Millions of motor-vehicle accidents happen each year due to human error (boredom, limited reaction times, limited reaction span, tiredness, mood, etc.). Self-driving vehicles can help avoid 90% of those accidents. It might take decades before fully automated vehicles on the roads of Europe become ubiquitous, however European Commission together with governments and companies is already taking active steps to facilitate this technology. According to 2020 Autonomous Vehicles Readiness Index (AVRI), European countries are among the most prepared for autonomous vehicles: The Netherlands ranked 2nd, Norway – 3rd, Finland – 5th, Sweden -6th, and so on.

As autonomous vehicle technology is entering a period of development maturity, fail-operational behavior becomes pivotal to bringing this technology to a wider audience. Fail-operational behavior is essential in handling safety-critical situations on its own, which directly impacts safety perception of AV users and the technology adoption rate. Bringing safe automated driving in urban and rural environments is one of the main factors for the PRYSTINE project.

PRYSTINE will realize Fail-operational Urban Surround perceptION (FUSION) which is based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments.

Furthermore, PRYSTINE will strengthen and extend traditional core competencies of the European industry, research organizations, and universities in smart mobility and in the electronic component and systems and cyber-physical systems domain.

1. Enhanced reliability and performance, reduced cost and power of FUSION components

2. Dependable embedded control by co-integration of signal processing and AI approaches for FUSION

3. Optimized electrical/electronic (E/E) architecture enabling FUSION-based automated vehicles

4. Fail-operational systems for urban and rural environments based on FUSION

PRYSTINE project has four key technical objectives (O1-O4), that address different levels (components, control systems, architectures and function) of the automation chain, and the non-technical objectives address market/social/technological impacts and “European Values”.

Objective 1: Components – Enhanced reliability and performance, cost and power of FUSION components

25% less data communication required compared to state-of-the-art
30% less false-positive detections compared to separate sensing approach
Fail-operational sensor compound vs. fail silent individual sensing approaches
Power reduction of 25% through semiconductor material improvements and functional convergence in sensor modules
Up to 30% cost reduction and 10% margin improvement for perception sub-systems


Objective 2: System – Dependable embedded control by co-integration of signal processing and AI approaches for FUSION

Fail-operational system approach for ADF (SAE Level 3+) vs. fail silent advanced driver assistance system (ADAS) approaches (SAE Levels up to 2)
Proposed Certification Approach for AI based sensor fusion, diagnostic, and control


Objective 3: Architecture – Dependable embedded control by cointegration of signal processing and AI approaches for FUSION

Fail-operational system architecture demonstrator for ADF (SAE Level 3+) vs. fail silent ADAS approaches (SAE Levels to 2)
LiDAR / RADAR sensor compound demonstrator


Objective 4: Automated Driving – Fail-operational systems for urban and rural environments based on FUSION

Demonstrators for fail-operational SAE Level 3+ ADFs in urban environments


Objective 5: Competitive advantage for European industry

Increasing market share and revenue of European companies through PRYSTINE’s ground-breaking technological advancements (O1-O4)


Objective 6: Increased user acceptance of automated driving functions

With such complex and challenging objectives full integration of all consortium members is integral as it shown the graph.